1. Field of the Invention
This invention relates to a membership data preparation method for fuzzy inference operation and an apparatus thereof, and an adaptation degree, operation method and apparatus thereof.
2. Discussion of the Related Art
A fuzzy inference operation is generally executed by a fuzzy rule of an IF-THEN type which consists of an antecedent starting with IF and a consequent starting with THEN. Each of the antecedent and consequent includes one or a plurality of propositions combined by AND or OR, each of the propositions consisting of an input variable and a membership function. A conventional storage of a conventional fuzzy inference operation device stores data representing membership functions in addition to data representing the rules.
There is well known a ROM reading method in which data representing a form of membership function is stored into ROM corresponding to a variable for each membership function. Since a result of antecedent adaptation degree operation is obtained only by reading function value data (degree of adaptation) from ROM, the antecedent adaptation degree operation can be executed at a high speed but a large capacity memory is requested to store all function value data into ROM in advance. Accordingly, the conventional method is not practical except a case where any high resolution of membership function is not necessary.
There is also well known a X/Y coordinate method in which a membership function is expressed by a polygonal line and a X and Y coordinate of a break point (inflection point) is stored into ROM for each membership function. According to the method, a storage capacity for storing X and Y coordinate data can be reduced, but an operation by software for a degree of adaptation takes a long time. If a hardware of an adaptation degree operation circuit is employed for a high speed operation, it is costly.
There is also well known a X/gradient method in which a membership function is expressed by a simple shape, such as a triangle or the like, and a X coordinate and left and right gradients of the vertex (its grade is always "1") of a triangle are stored into ROM for each membership function. The method employs gradient data for a high speed operation, and does not employ division for an adaptation degree operation. This method also cannot remarkably reduce the capacity of ROM. For example, when seven kinds of membership functions are set for each of input variables which are eight kind of variables, a memory having 200 bytes is necessary, and a fuzzy inference operation device is limited for minimizing a cost.